Low back and neck pain are two of the most common medical problems. In a recent study, 26.4% of individuals had an episode of severe low back pain and 13.8% severe neck pain in the preceding 3 months. Moreover, low back or neck pain is the major complaint in 3% of all office visits to primary care physicians (PCPS), and 5% of all healthcare visits overall. Although many patients suffer from musculoskeletal complaints due to deconditioning, a large fraction has nerve root compression (radiculopathy) requiring different treatment paradigms. Discriminating between these two on history and examination alone is challenging. Many of these patients undergo imaging of the spine with MRI and subspecialist referral, incurring additional costs. Thus, a diagnostic tool for PCPs could improve care and reduce costs. One technology that may help physicians correctly diagnose the cause of back or neck pain is electrical impedance myography (EIM). Like needle electromyography (EMG), EIM can give assessment of muscle health in both limbs and paraspinal musculature. Unlike EMG, however, EIM is very fast to perform, requires limited training, and is non-invasive, painless, and quantitative. Moreover, unlike EMG, it can also provide data on the degree of deconditioning affecting a given muscle. For these reasons, and previously published data, we hypothesize that EIM will aid physicians in the initial classification of low back or neck pain as radiculopathic or musculoskeletal in nature. We believe this will result in reduced overall costs and improved outcomes since patients will receive the right therapy sooner. Convergence Medical Devices, Inc. (CMD) has as its primary focus development of EIM technology. Using Phase 1 SBIR and additional funds we have developed an advanced EIM prototype and shown its ability to distinguish between healthy and diseased muscle. In this Phase 2 application, we propose to refine EIM for office-based assessment of back and neck pain, with the goal of improving patient outcomes and reducing costs. We will achieve this through the following aims: (1) We will collect EIM data from multiple muscles on 120 healthy subjects (including 50 completed prior to grant initiation), 60 with expert-defined radiculopathy and 60 with musculoskeletal back pain in order to develop algorithms to aid physicians in diagnosing neck/back pain; (2) We will refine our EIM software to facilitate interpretation by primary care physicians and their staff; and (3) we will tst ease-of-use, comfort, and preliminarily assess EIM's ability to improve a physician's ability to diagnose back and neck pain in a clinical setting. With the completion of these aims, CMD, will be well-poised submit a 510k application to FDA and pursue Phase 3 funding for commercialization.